Intergeneration Division Based on Key Component Analysis in an Autonomous Transportation System Using the Natural Language Processing Method

Figure 3

LDA2vec is a combination of LDA and word2vec. The topic vector is generated from the inverse result of the text generation method based on the Dirichlet distribution parameters and . With a membership parameter , the topic vector generates the document vector. The pivot word vector is obtained from skip-gram in word2vec. We combine the two vectors to get the context vector and compare with the target word vector to get an unsupervised learning result.